Across
- 3. Improving patient care by identifying risk factors and potential treatment outcomes.
- 5. Aspects of Data Mining
- 7. Detecting fraudulent transactions and credit card fraud.
- 8. Data is gathered, cleansed (scrubbed for outliers), and then analyzed for patterns.
Down
- 1. Common methods include classification (classifying data into groups), clustering (grouping similar data points), regression (predicting numerical values), and association rule mining (finding relationships between variables).
- 2. Analyzing customer behavior to personalize experiences and target campaigns.
- 4. Optimizing production processes and reducing equipment downtime.
- 6. Increased revenue, improved operational efficiency, better risk management, and strengthened competitive advantage.